Citation

Lopez AB, Jin WL, Faruque MAA. IEEE Trans. Intel. Transp. Syst. 2022; 23(8): 13255-13264.

Copyright

(Copyright © 2022, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TITS.2021.3123193

PMID

unavailable

Abstract

With newer technologies, the embedded hardware and software in traditional vehicles and traffic control infrastructure continue to become more interconnected and more vulnerable. To assist in dealing with existing and potential vulnerabilities, we present a novel attack modeling methodology, taxonomy, and metrics (relative average waiting time, average network flow, impacts and rate of changes) to model, simulate, and meaningfully evaluate the security of Intelligent Transportation Systems. We implement our work in two different architectures: 1) Newell's Car-Following Model with Bounded Acceleration (the BA-Newell Model) in Matlab and 2) Intelligent Driver Model in Veins. Our code is entirely open-sourced and will be maintained so that the ITS community may use it as a tool. We observe that the architectural-related metric values for sample attack simulation results are similar and transferable; where, for example, the rate of change values have range of average distances 1.8-3.5% for network flow impact and 3.3-9.6% for wait time impact.

Language: en

Keywords

communications technology; computer networks; Intelligent Transportation Systems (ITS); intelligent vehicles; Mathematical models; Measurement; network security; Roads; Safety; Sensors; Taxonomy; Vehicle-to-everything